
"""simple docstring"""


import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 	__a	(   _lowerCAmelCase     ,  unittest.TestCase						):
       UpperCamelCase_		:       List[str]				=      LayoutLMTokenizer
       UpperCamelCase_		:       Any				=      LayoutLMTokenizerFast
       UpperCamelCase_		:       Union[str, Any]				=      True
       UpperCamelCase_		:       Dict				=      True






       def 						_SCREAMING_SNAKE_CASE							(	self			:				str      )->	int:







              """simple docstring"""
              super().setUp()

              UpperCamelCase       			=		[
                  "[UNK]",
                  "[CLS]",
                  "[SEP]",
                  "want",
                  "##want",
                  "##ed",
                  "wa",
                  "un",
                  "runn",
                  "##ing",
                  ",",
                  "low",
                  "lowest",
              ]
              UpperCamelCase       			=		os.path.join(self.tmpdirname							,   VOCAB_FILES_NAMES["vocab_file"]      )
              with open(self.vocab_file							,   "w"							,   encoding="utf-8"      ) as vocab_writer:
                     vocab_writer.write("".join([x + "\n" for x in vocab_tokens]      )      )






       def 						_SCREAMING_SNAKE_CASE							(	self			:				Optional[Any]							,   **UpperCAmelCase_			:				Tuple      )->	str:







              """simple docstring"""
              return LayoutLMTokenizer.from_pretrained(self.tmpdirname							,   **UpperCAmelCase_      )






       def 						_SCREAMING_SNAKE_CASE							(	self			:				int							,   UpperCAmelCase_			:				Optional[Any]      )->	Optional[Any]:







              """simple docstring"""
              UpperCamelCase       			=		"UNwant\u00E9d,running"
              UpperCamelCase       			=		"unwanted, running"
              return input_text, output_text






       def 						_SCREAMING_SNAKE_CASE							(	self			:				str      )->	Tuple:







              """simple docstring"""
              UpperCamelCase       			=		self.tokenizer_class(self.vocab_file      )

              UpperCamelCase       			=		tokenizer.tokenize("UNwant\u00E9d,running"      )
              self.assertListEqual(UpperCAmelCase_							,   ["un", "##want", "##ed", ",", "runn", "##ing"]      )
              self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_      )							,   [7, 4, 5, 10, 8, 9]      )






       def 						_SCREAMING_SNAKE_CASE							(	self			:				List[Any]      )->	Dict:







              """simple docstring"""
              pass







"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_yolos import YolosImageProcessor


SCREAMING_SNAKE_CASE			  =  logging.get_logger(__name__)



class 	__a	(   _lowerCAmelCase						):






       def __init__(	self			:				str							,   *UpperCAmelCase_			:				str							,   **UpperCAmelCase_			:				Any      )->	None:







              """simple docstring"""
              warnings.warn(
                  "The class YolosFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
                  " use YolosImageProcessor instead."							,   UpperCAmelCase_							,   )
              super().__init__(*UpperCAmelCase_							,   **UpperCAmelCase_      )





